Radiometric Calibration for Multispectral Camera of Different Imaging Conditions Mounted on a UAV Platform

作者：Yahui Guo, J. Senthilnath, Wenxiang Wu, Xueqin Zhang, Zhaoqi Zeng, Han Huang · 发表于：Sustainability · 年份：2019 · DOI：10.3390/su11040978 · 被引用次数：142 · 研究领域：Remote Sensing in Agriculture、Calibration and Measurement Techniques、Remote Sensing and LiDAR Applications

Unmanned aerial vehicle (UAV) equipped with multispectral cameras for remote sensing (RS) has provided new opportunities for ecological and agricultural related applications for modelling, mapping, and monitoring. However, when the multispectral images are used for the quantitative study, they should be radiometrically calibrated, which accounts for atmospheric and solar conditions by converting the digital number into a unit of scene reflectance that can be directly used in quantitative remote sensing (QRS). Indeed, some of the present applications using multispectral images are processed without precise calibration or with coarse calibration. The radiometric calibration of images from the UAV platform is quite difficult to perform, as the imaging condition is different for every single image. Thus, a standard procedure is necessary for a systematical radiometric calibration method to generate multispectral images with unit reflectance. Further, these images can be used to calculate vegetation indices, which are useful in monitoring vegetation phenology. These vegetation indices are considered as a potential screening tool to know the plant status, such as nitrogen, chlorophyll content, green leaf biomass, etc. This study focuses on a series of radiometric calibrations for multispectral images acquired from different flight altitudes, time instants, and weather conditions. Radiometric calibration for multispectral images is performed using the linear regression method (LRM)....